For this assignment, you will create Ruby source files containing functions implementing each of the problems described below. If you find it useful for any of the problems in this assignment, you may define additional helper functions that your primary function for that problem calls to solve a sub-problem. Definitions for these helper functions should be included in the same Ruby source file as the primary function they help. You should store a source file for each problem in a folder named pa6.
Note: You are responsible for protecting your solutions to these problems from being seen by other students either physically (e.g., by looking over your shoulder) or electronically. (More information can be found in the instructions for Programming Assignment 2.)
[4 points] Recall that, one way to represent the nodes of a complete binary tree is with an array, where the first element contains the root, the next two elements contain the next level of the tree (the children of the root), the next four elements contain the next level of the tree (two containing the children of the root's left child and two containing the children of the root's right child), the next eight elements contain the next level (the two children of each of the nodes at the previous level), and so on, depending on how many levels the tree has.
The binary tree above with nodes labeled with strings "alpha", "bravo", ... would be represented by the Ruby array:
["alpha", "bravo", "charlie", "delta", "echo", "foxtrot", "golf", "hotel", "india", "juliet", "kilo", "lima", "mike", "nova", "oscar"] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Let us look at the indices of left children:
Do you see a pattern? There are simple formulas that can be used to calculate the indices of a node's left child, right child, and parent from that node's index.
Define a function left_index(index) (in left_index.rb) that, when passed the index of a node, will return the index of that node's left child. (You do not need to worry about whether the node has a left child; when the node does not actually have a left child, the function should still return where its left child would be if it had one. You may assume that index is a non-negative integer.)
Define a function right_index(index) (in
right_index.rb) that, when passed the index of a node,
will return the index of that node's right child.
(You do not need to worry about whether the node has a right
child; when the node does not actually have a right child, the
function should still return where its right child would
be if it had one. You may assume that
Define a function parent_index(index) (in parent_index.rb) that, when passed the index of a node, will return the index of that node's parent. (You may assume that the index is a positive integer.)
Define a function leaf?(tree, index) (in leaf.rb ) that, when passed the array representation tree of a complete binary tree and the index of a node index, will return true if the node has no children and false otherwise (a node with no children is called a leaf). You may assume that index is a non-negative index less than the length of tree . You may want to use some of the functions you defined in the previous parts.
Example usage:
>> a = ["alpha", "bravo", "charlie", "delta", "echo", "foxtrot", "golf", "hotel", "india", "juliett", "kilo", "lima", "mike", "nova", "oscar"] => ["alpha", "bravo", "charlie", "delta", "echo", "foxtrot", "golf", "hotel", "india", "juliett", "kilo", "lima", "mike", "nova", "oscar"] >> leaf?(a,0) => false >> leaf?(a,13) => true
The array representation for binary trees can be extended to incomplete trees by using nil to represent the "missing" nodes that would need to be added to make a complete tree.
For example, the binary tree above can be represented by the Ruby array
["alpha", "bravo", "charlie", "delta", "echo", "foxtrot", nil , "hotel", "india", "juliett", nil, "lima", "mike", nil , nil ] 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14Note that since missing children can always be represented by nil, the tree ["alpha"] is the same as the tree ["alpha", nil, nil].
[1 point] The descendants of a node \(p\) in a tree are defined to include all the nodes that are on a path from the node \(p\), excluding \(p\) itself. For example, in the incomplete tree above, the descendants of the node with label "charlie" consist of the nodes with labels "foxtrot", "lima", and "mike". In this question you will write a recursive function num_descendants(tree,i), which requires an array tree encoding a binary tree as described above and an index i of a node in the binary tree. When called, num_descendants(tree,i) should return the number of descendants of the node at index i.
The following algorithm counts the number of descendants of the node at index i in the array tree, which is an array representation of a non-empty, possibly incomplete binary tree.
In num_descendants.rb, using the algorithm above, define a function num_descendants(tree,i), which requires an array tree encoding a binary tree as described above and an index i of a node in the binary tree. When called, num_descendants(tree,i) should return the number of descendants of the node at index i. You can assume that the function will always be called with a "correct" array representation, so if a node is nil, the array entries where its children would be located will also be nil.
Example usage:>> num_descendants(a,0) # alpha has 10 descendants => 10 >> num_descendants(a,2) # charlie has 3 descendants => 3 >> num_descendants(a,7) # hotel has no descendants => 0
Example usage:
>> a = ["alpha", "bravo", "charlie", "delta", "echo", "foxtrot", nil, "hotel", "india", "juliet", nil, "lima", "mike", nil, nil] => ["alpha", "bravo", "charlie", "delta", "echo", "foxtrot", nil, "hotel", "india", "juliett", nil, "lima", "mike", nil, nil] >> missing_child(a, 0) => ["echo", "charlie"] >> missing_child(a, 1) => ["echo"] >> missing_child(a, 2) => ["charlie"] >> b = ["apple", "banana", "cherry", nil, "date", nil, nil] => ["apple", "banana", "cherry", nil, "date", nil, nil] >> missing_child(b, 0) # draw the tree b to check the answer => ["banana"] >> c = ["aardvark", "bear", nil, "cat", "dog", nil, nil, "eel", nil] => ["aardvark", "bear", nil, "cat", ""dog", nil, nil "eel", nil] >> missing_child(c, 0) # draw the tree c to check the answer => ["aardvark", "cat"]You should solve this problem in stages:
[2 points] In a Binary Search Tree, each node has a value that is greater than that of all of the nodes reachable through its left child and that is less than that of all of the nodes reachable through its right child. The examples below is a binary search tree. (We will assume that the tree does not hold two nodes with the same value.)
The following is an algorithm for searching an array tree encoding a binary search tree to determine whether it contains a node with the value key.
Define a function bst_search?(tree,key) (in bst_search.rb) that uses this algorithm to determine whether the value key occurs in tree, the array representing a binary search tree. Call the functions left_index and right_index that you defined in problem 1 to set curr_index in substeps C and D above.
Example usage:
>> bstree = [84,41,96,24,52,91,98,10,26,43,nil,85,94,nil,nil] => [84,41,96,24,52,91,98,10,26,43,nil,85,94,nil,nil] >> bst_search?(bstree, 52) => true >> bst_search?(bstree, 51) => false >> bst_search?(bstree, 41) => true >> bst_search?(bstree, 97) => false
[1 point] (corrected) Recall that a graph of \(n\) nodes can be represented as an \(n \times n\) matrix where the value at row \(i\) column \(j\) gives the "cost" of going directly from node \(i\) to node \(j\) in the graph.
In file min_local.rb write a Ruby function min_local(g,index) that, when passed a graph g and index returns the minimum cost of going from the node with index directly to another node.
Hints:
You can represent infinite edge weights by
using the expression 1.0/0.0
which evaluates to
a special floating point number that is treated as being
larger than any other floating point number (i.e. infinity).
Use this inf value to represent the weight of going from a node to itself.
Example usage:
>> inf = 1.0/0.0 => Infinity >> G = [[inf,6,7,5], [6,inf,4,inf], [7,4,inf,3], [5,inf,3,inf]] => [[Infinity,6,7,5], [6,Infinity,4,Infinity], [7,4,Infinity,3], [5,Infinity,3,Infinity]] >> min_local(G, 0) => 5 >>min_local(G,2) => 3
You should now have a pa6 directory, containing:
Zip up your directory and upload it using the autolab system. (The autolab system will accept submissions beginning on Friday until the deadline Tuesday night.)